TheSequence
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RL-series goes on
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the most useful free ML&AI newsletter
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What’s New in AI, a deep dive into one of the freshest research papers or technology frameworks that is worth your attention. Our goal is to keep you u…
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In this issue: we explore policy optimization in reinforcement learning methods; we learn how Google Research uses reinforcement learning to master foo…
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Mobile deep learning is one of those things that looks cool and simple from the outside and becomes a royal nightmare when you get into it.
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It’s so inspiring to learn from practitioners. Getting to know the experience gained by researchers, engineers, and entrepreneurs doing real ML work is…
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Interviews
François CholletKeras, TensorFlow and New Ways to Measure Machine Intelligence
Adam Wenchel/Arthur AIAbout ML explainability, interpretability, and fairness
Hyun Kim/CEO of Superb AIon true data labeling automation
Mike Del Balso/Tecton"There is too much depth in this space for feature stores to be just a “feature”
Iskandar Sitdikov/ProvectusHealthcare has it all: NLP, computer vision, recommendations, and a whole lot more
H.O. Maycotte/CEO of Molecula on shifting from “data as fuel” to “features as fuel”
Manu Sharma/Labelbox The future of data labeling automation
Jim Dowling/Logical Clocks ABThe future of feature stores
Justin Harris/Microsoft"My vision is for people to be compensated for the data they provide while keeping models free to use"
Jan Beitner/PyTorch Forecasting" I believe deep learning models will become the method of choice for time-series forecasting"
Krishna Gade/FiddlerChallenges with model explainability
William FalconWe did our job right if the term MLOps disappears
Recap
⏳⌛️Time-Series Forecasting Wrap-Up

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